Sales prediction for a pharmaceutical distribution company: a data mining based approach | Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data mining

Detalhes bibliográficos
Autor(a) principal: Ribeiro, Augusto
Data de Publicação: 2016
Outros Autores: Seruca, Isabel, Durão, Natércia
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/11328/1750
Resumo: For pharmaceutical distribution companies it is essential to obtain good estimates of medicine needs, due to the short shelf life of many medicines and the need to control stock levels, so as to avoid excessive inventory costs while guaranteeing customer demand satisfaction, and thus decreasing the possibility of loss of customers due to stock outages. In this paper we explore the use of the time series data mining technique for the sales prediction of individual products of a pharmaceutical distribution company in Portugal. Through data mining techniques, the historical data of product sales are analyzed to detect patterns and make predictions based on the experience contained in the data. The results obtained with the technique as well as with the proposed method suggest that the performed modelling may be considered appropriate for the short term product sales prediction.
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spelling Sales prediction for a pharmaceutical distribution company: a data mining based approach | Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data miningmedicinesstock unavailabilitydata miningtime seriessales predictionFor pharmaceutical distribution companies it is essential to obtain good estimates of medicine needs, due to the short shelf life of many medicines and the need to control stock levels, so as to avoid excessive inventory costs while guaranteeing customer demand satisfaction, and thus decreasing the possibility of loss of customers due to stock outages. In this paper we explore the use of the time series data mining technique for the sales prediction of individual products of a pharmaceutical distribution company in Portugal. Through data mining techniques, the historical data of product sales are analyzed to detect patterns and make predictions based on the experience contained in the data. The results obtained with the technique as well as with the proposed method suggest that the performed modelling may be considered appropriate for the short term product sales prediction.AISTI | ULPG2017-02-10T18:20:43Z2016-01-01T00:00:00Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/11328/1750porRibeiro, AugustoSeruca, IsabelDurão, Natérciainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-06-15T02:10:01ZPortal AgregadorONG
dc.title.none.fl_str_mv Sales prediction for a pharmaceutical distribution company: a data mining based approach | Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data mining
title Sales prediction for a pharmaceutical distribution company: a data mining based approach | Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data mining
spellingShingle Sales prediction for a pharmaceutical distribution company: a data mining based approach | Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data mining
Ribeiro, Augusto
medicines
stock unavailability
data mining
time series
sales prediction
title_short Sales prediction for a pharmaceutical distribution company: a data mining based approach | Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data mining
title_full Sales prediction for a pharmaceutical distribution company: a data mining based approach | Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data mining
title_fullStr Sales prediction for a pharmaceutical distribution company: a data mining based approach | Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data mining
title_full_unstemmed Sales prediction for a pharmaceutical distribution company: a data mining based approach | Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data mining
title_sort Sales prediction for a pharmaceutical distribution company: a data mining based approach | Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data mining
author Ribeiro, Augusto
author_facet Ribeiro, Augusto
Seruca, Isabel
Durão, Natércia
author_role author
author2 Seruca, Isabel
Durão, Natércia
author2_role author
author
dc.contributor.author.fl_str_mv Ribeiro, Augusto
Seruca, Isabel
Durão, Natércia
dc.subject.por.fl_str_mv medicines
stock unavailability
data mining
time series
sales prediction
topic medicines
stock unavailability
data mining
time series
sales prediction
description For pharmaceutical distribution companies it is essential to obtain good estimates of medicine needs, due to the short shelf life of many medicines and the need to control stock levels, so as to avoid excessive inventory costs while guaranteeing customer demand satisfaction, and thus decreasing the possibility of loss of customers due to stock outages. In this paper we explore the use of the time series data mining technique for the sales prediction of individual products of a pharmaceutical distribution company in Portugal. Through data mining techniques, the historical data of product sales are analyzed to detect patterns and make predictions based on the experience contained in the data. The results obtained with the technique as well as with the proposed method suggest that the performed modelling may be considered appropriate for the short term product sales prediction.
publishDate 2016
dc.date.none.fl_str_mv 2016-01-01T00:00:00Z
2016
2017-02-10T18:20:43Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/11328/1750
url http://hdl.handle.net/11328/1750
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv AISTI | ULPG
publisher.none.fl_str_mv AISTI | ULPG
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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repository.mail.fl_str_mv
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